Alternative data solutions: footfall and geospatial data

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Alternative data helps investors make better, faster decisions with their investment strategies. It includes things like geospatial data, footfall data, credit card transactions, and even social media information.


Alternative data is generated by three sources: people, processes, and sensors. Where traditional data is produced by companies, alternative data is collected through various web traffic and digital channels, including GPS data from mobile phones.

Alternative data covers a lot of ground and so does geospatial. Below, we'll take a closer look at alternative data solutions and explore how they can be used by finance companies, insurers, and others to improve their businesses. Specifically, we'll look at how to apply raw data from geographic information systems to inform investment opportunities.

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Geospatial technology and remote sensing

Geospatial technology helps companies map and analyze geographic location data. This data can include satellite imagery, census data, raster data (think: satellite imagery), and GPS data gathered from mobile phones and apps.

Geospatial tools and location data equals a new world of data analytics insight that empowers companies to understand spatial relationships and human mobility as it affects their business. The key element to this is acquisition of clean, fresh geospatial data from a reputable source.

Geospatial data to augment business data

Nearly everything from the places we go, to the people we encounter, to the brands we buy from is recorded in geospatial databases. There are a number of vibrant data sources available to work with, including both commercial and open source solutions.

Geospatial data has natural confluence with many other forms of both public and business data. When one is used to augment the other, the resulting stream is a flow of real world insights that inform investment decisions, detect change sooner, and measure its effects.

To do these things though, geospatial data must first be rendered useful to the task at hand by isolating particular areas or locations. That's where trade areas and points of interest (POIs) come in.

Trade Areas vs POIs

A trade area is defined as the geographic distance where retail customers come from. A trade area can be drawn using custom polygons to set specific limits on the areas you want to measure.

GPS location data can help retailers better understand their trade areas in ways not accessible via conventional methods. This richer understanding would enable retailers to make more informed business decisions. Typically, a trade area is broken down into three components:

  • Primary: 10% of your customers are within this radius
  • Secondary: 30% of your customers are within this radius
  • Tertiary: 60% of your customers are within this radius

POIs, on the other hand, are locations that lots of people visit either routinely, seasonally, or based on certain events. Examples of a POI include:

  • Arenas and stadiums
  • Civic centers
  • Retail stores
  • Restaurants

POIs give us important reference points for assessing, planning and decision-making. How people move around a location provides important insight for a variety of industries and job roles. This information is valuable for data scientists, retailers, city planners, commercial real estate investors, healthcare providers, and lots more.

Footfall data and geospatial analysis

Footfall analytics can give businesses a holistic picture of customer movement by interpreting mobility data. The data that is most helpful tends to be:

  • The number of consumers visiting your business
  • The percentage of people in the area that visit your business, known as the capture rate
  • The patterns for when people visit your business (hourly, daily, weekly, monthly)
  • The amount of time people spend visiting your business
  • Do people come back and stay loyal to your business?
  • The demographics of consumers such as age, gender, income group and education level


Geospatial data analysis use cases

Alternative data sets including geospatial are routinely applied in a wide range of use cases across a spectrum of industries, including finance, insurance, telecommunications, retail and health.

Fortune 500 insurers use a set custom metrics to tie a through line between identified risk and the number of claims submitted. What’s more, they were able to confirm which times, days, and seasons were most likely to result in increased claims.

“While location data is one piece of the puzzle, we believe that it paints a holistic picture helping us generate more accurate quotes.”

– Chief Underwriting Officer, Property and Casualty Insurer


Leading home builders identify income trends across regions, and select areas with prime growth opportunities to understand regional differences in behavior. Digging into residents’ behavioral patterns helps tie a through line across data sources spanning rural, urban, and suburban areas.

"We believe we've set ourselves up for success to weather the pending storm regardless of its status as a recession or correction. We feel more confident knowing we have the data we need at our disposal.”

– Market Intelligence Director, National Home Building Company


Retailers
use geospatial data streams combined with business information to inform new site selections and marketing campaigns, or to set hours, staffing levels and product mix. Retailers and restaurateurs pay particularly strong attention to trade area and footfall data around their POIs.

"Geospatial is more important than ever because it takes data integration to the next level to account for evolving shopping habits and provide retailers the necessary insights to adjust operations and customer engagement accordingly."

- VP Global Solutions, sensor company


If you'd like to learn more about geospatial as an alternative data source for your business, please contact us today.

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